Digital Commons Network^™

Modeling And Analysis Of Intracellular Signaling Networks And Cellular Decisions, Mustafa Ozen

Dissertations

Developing molecular network analysis methods is important due to their applications on complex biological systems such as target discovery, development of drugs, discovering drug effects, and finding treatments for many complex diseases, e.g., cancer, autoimmune, and mental disorders. An example of analysis techniques is the fault diagnosis analysis, in which the purpose is to quantify how much vulnerable the entire network is to dysfunction of one or multiple molecules. Such analysis can be done after proper network models are implemented, trained, and tested against the experimental data. In this dissertation, a Boolean modeling framework is implemented and methods to train …

Machine Learning Models For Deciphering Regulatory Mechanisms And Morphological Variations In Cancer, Saman Farahmand

Graduate Doctoral Dissertations

The exponential growth of multi-omics biological datasets is resulting in an emerging paradigm shift in fundamental biological research. In recent years, imaging and transcriptomics datasets are increasingly incorporated into biological studies, pushing biology further into the domain of data-intensive-sciences. New approaches and tools from statistics, computer science, and data engineering are profoundly influencing biological research. Harnessing this ever-growing deluge of multi-omics biological data requires the development of novel and creative computational approaches. In parallel, fundamental research in data sciences and Artificial Intelligence (AI) has advanced tremendously, allowing the scientific community to generate a massive amount of knowledge from data. Advances …

Differentiating Human Embryonic Stem Cells In Micropatterns To Study Cell Fate Specification And Morphogenetic Events During Gastrulation, Kyaw Thu Minn

McKelvey School of Engineering Graduate Student Theses & Dissertations

During mammalian embryogenesis, the first major lineage segregation occurs when embryonic epiblast, and extraembryonic trophectoderm and hypoblast arise in the blastocyst. In the next fundamental and conserved phase of animal embryogenesis known as gastrulation, extraembryonic cells provide signals to epiblast to instruct embryonic patterning, and epiblast gives rise to germ layers ectoderm, mesoderm, and endoderm, that will establish all embryonic tissues. Proper specification and morphogenesis of germ layers during gastrulation is vital for correct embryonic development. Due to ethical and legal restrictions limiting human embryo studies, human gastrulation is poorly understood. Our knowledge of human gastrulation has largely been derived …

Analysis Of Protein-Protein Interaction Network From Leukocyte Transcriptomic Profiles In Severe Covid -19 Patients, Pakorn Sagulkoo

Chulalongkorn University Theses and Dissertations (Chula ETD)

Coronavirus disease 2019 (COVID-19) still provides global public health issues although several vaccines and antiviral agents have been developed. Some patients experience severe conditions needed medical intensive care, and some are dead due to the failure of treatments. Therefore, identifying the key genes and underlying molecular mechanisms is necessary to discover precisely targeted drugs. Analysis of protein-protein interaction (PPI) networks provides invaluable information to find disease mechanisms and effective alternative drugs. Hence, PPI network analysis based on leukocyte transcriptomic profiles of severe COVID-19 collected from Gene Expression Omnibus (GEO) DataSets was proposed for this study. A network diffusion method called …

Development Of Computational To Ols To Target Microrna, Luo Song

Dissertations and Theses (Open Access)

MicroRNAs (a.k.a, miRNAs) play an important role in disease development. However, few of their structures have been determined and structure-based computational methods remain challenging in accurately predicting their interactions with small molecules. To address this issue, my thesis is to develop integrated approaches to screening for novel inhibitors by targeting specific structure motifs in miRNAs. The project starts with implementing a tool to find potential miRNA targets with desired motifs. I combined both sequence information of miRNAs and known RNA structure data from Protein Data Bank (PDB) to predict the miRNA structure and identify the motif to target, then I …

Machine Learning Applications For Drug Repurposing, Hansaim Lim

Dissertations, Theses, and Capstone Projects

The cost of bringing a drug to market is astounding and the failure rate is intimidating. Drug discovery has been of limited success under the conventional reductionist model of one-drug-one-gene-one-disease paradigm, where a single disease-associated gene is identified and a molecular binder to the specific target is subsequently designed. Under the simplistic paradigm of drug discovery, a drug molecule is assumed to interact only with the intended on-target. However, small molecular drugs often interact with multiple targets, and those off-target interactions are not considered under the conventional paradigm. As a result, drug-induced side effects and adverse reactions are often neglected …

Methods To Integrate Genetic And Clinical Data For Disease Subtyping, Diana Mabel Diaz-Herrera

Wayne State University Dissertations

Enormous efforts have been made to collect genetic and clinical data from cancer patients to advance the understanding of disease development and progression. Processing and analyzing these flows of data is challenging. Many computational methods have been proposed to help different fronts of biology and medicine. The integration of clinical and genetic data using computational methods towards personalized medicine is considered the future for oncology studies, and this thesis contributes in this direction. This thesis presents three new data integration approaches to elucidate granular and meaningful disease sub-types from high-dimensional complex genetic and clinical variables, which is an essential step …

Biological And Computational Studies Of The Structure And Function Of Pul103, A Human Cytomegalovirus Tegument Protein, Ashley N. Anderson

Wayne State University Dissertations

Human cytomegalovirus (HCMV) is an enveloped, single segment, double-stranded DNA virus. HCMV infection causes disease in immunocompromised (HIV patients, transplant recipients) and immunodeficient (fetuses, neonates) populations. Current treatments are effective but are either limited in use or can lead to organ damage and/or antiviral resistance, and no vaccines are available. Additional antiviral targets are needed. HCMV pUL103 is a potential antiviral target. pUL103 is a conserved herpesvirus protein present in the tegument, layer of proteins and RNA between the envelope and capsid of HCMV virions. pUL103 helps reorganize cellular secretory machinery (Golgi, endosomes) to form the cytoplasmic virion assembly compartment …

Designing And Sample Size Calculation In Presence Of Heterogeneity In Biological Studies Involving High-Throughput Data., Sudhir Srivastava

Electronic Theses and Dissertations

The designing and determination of sample size are important for conducting high-throughput biological experiments such as proteomics experiments and RNA-Seq expression studies, thus leading to better understanding of complex mechanisms underlying various biological processes. The variations in the biological data or technical approaches to data collection lead to heterogeneity for the samples under study. We critically worked on the issues of technical and biological heterogeneity. The quantitative measurements based on liquid chromatography (LC) coupled with mass spectrometry (MS) often suffer from the problem of missing values (MVs) and data heterogeneity. We considered a proteomics data set generated from human kidney …

Mrub_3020, A Paralog Of Mrub_1489, Is Orthologous To E. Coli Casc (Locus Tag B2761), Alfred Dei-Ampeh, Dr. Lori Scott

Meiothermus ruber Genome Analysis Project

This project is part of the Meiothermus ruber genome analysis project, which uses a collection of online bioinformatics tools to predict gene function. We investigated the biological functions of two genes: mrub_3020 and mrub_1489. We make two hypotheses in this investigation: a) mrub_3020 is orthologous to the gene b2761 in E. coli K12 MG1655 (a.k.a. casC); b) mrub_1489 is a paralog of mrub_3020. We also predict that the two genes encode unique proteins: mrub_3020 with DNA coordinates 3060491…3063190 encodes a CRISPR – associated helicase (Cas3) that supports the Cascade complex of the CRISPR – Cas adaptive immune system …

Deciphering The Role Of Human Arylamine N-Acetyltransferase 1 (Nat1) In Breast Cancer Cell Metabolism Using A Systems Biology Approach., Samantha Marie Carlisle

Electronic Theses and Dissertations

Background: Human arylamine N-acetyltransferase 1 (NAT1) is a phase II xenobiotic metabolizing enzyme found in almost all tissues. NAT1 can additionally hydrolyze acetyl-coenzyme A (acetyl-CoA) in the absence of an arylamine substrate. NAT1 expression varies inter-individually and is elevated in several cancers including estrogen receptor positive (ER+) breast cancers. Additionally, multiple studies have shown the knockdown of NAT1, by both small molecule inhibition and siRNA methods, in breast cancer cells leads to decreased invasive ability and proliferation and decreased anchorage-independent colony formation. However, the exact mechanism by which NAT1 expression affects cancer risk and progression remains unclear. Additionally, consequences …

A Cure For Salmonella: Engaging Students In Pathogen Microbiology And Bioinformatics, Sophie Jurgensen

Senior Honors Projects, 2010-2019

Advances in Next Generation Sequencing (NGS) technology have generated a vast amount of publicly available genomic data, creating a need for students with training in computational analysis. This laboratory lesson is a course-based undergraduate research experience (CURE) focusing on environmental Salmonella, a common foodborne pathogen that is of great interest to public health laboratories but is relatively less virulent than most other such pathogens. As discovery is a central tenet of CUREs, students isolate novel Salmonella enterica and related strains from stream sediment, poultry litter, or other sources in the first half of the lesson (Module 1). They also …

Novel Computational Methods For Sequencing Data Analysis: Mapping, Query, And Classification, Xinan Liu

Theses and Dissertations--Computer Science

Over the past decade, the evolution of next-generation sequencing technology has considerably advanced the genomics research. As a consequence, fast and accurate computational methods are needed for analyzing the large data in different applications. The research presented in this dissertation focuses on three areas: RNA-seq read mapping, large-scale data query, and metagenomics sequence classification.

A critical step of RNA-seq data analysis is to map the RNA-seq reads onto a reference genome. This dissertation presents a novel splice alignment tool, MapSplice3. It achieves high read alignment and base mapping yields and is able to detect splice junctions, gene fusions, and circular …

Ultra-Fast And Memory-Efficient Lookups For Cloud, Networked Systems, And Massive Data Management, Ye Yu

Theses and Dissertations--Computer Science

Systems that process big data (e.g., high-traffic networks and large-scale storage) prefer data structures and algorithms with small memory and fast processing speed. Efficient and fast algorithms play an essential role in system design, despite the improvement of hardware. This dissertation is organized around a novel algorithm called Othello Hashing. Othello Hashing supports ultra-fast and memory-efficient key-value lookup, and it fits the requirements of the core algorithms of many large-scale systems and big data applications. Using Othello hashing, combined with domain expertise in cloud, computer networks, big data, and bioinformatics, I developed the following applications that resolve several major …

Lichen Conservation In Eastern North America: Population Genomics, Climate Change, And Translocations, Jessica Allen

Dissertations, Theses, and Capstone Projects

Conservation biology is a scientific discipline that draws on methods from diverse fields to address specific conservation concerns and inform conservation actions. This field is overwhelmingly focused on charismatic animals and vascular plants, often ignoring other diverse and ecologically important groups. This trend is slowly changing in some ways; for example, increasing number of fungal species are being added to the IUCN Red-List. However, a strong taxonomic bias still exists. Here I contribute four research chapters to further the conservation of lichens, one group of frequently overlooked organisms. I address specific conservation concerns in eastern North America using modern methods. …

Network Exploration Of Correlated Multivariate Protein Data For Alzheimer's Disease Association, Matthew J. Lane

Theses

Alzheimer Disease (AD) is difficult to diagnose by using genetic testing or other traditional methods. Unlike diseases with simple genetic risk components, there exists no single marker determining as to whether someone will develop AD. Furthermore, AD is highly heterogeneous and different subgroups of individuals develop the disease due to differing factors. Traditional diagnostic methods using perceivable cognitive deficiencies are often too little too late due to the brain having suffered damage from decades of disease progression. In order to observe AD at early stages prior to the observation of cognitive deficiencies, biomarkers with greater accuracy are required. By using …

Global Gene Expression Profiling Of Healthy Human Brain And Its Application In Studying Neurological Disorders, Simarjeet K. Negi

Theses & Dissertations

The human brain is the most complex structure known to mankind and one of the greatest challenges in modern biology is to understand how it is built and organized. The power of the brain arises from its variety of cells and structures, and ultimately where and when different genes are switched on and off throughout the brain tissue. In other words, brain function depends on the precise regulation of gene expression in its sub-anatomical structures. But, our understanding of the complexity and dynamics of the transcriptome of the human brain is still incomplete. To fill in the need, we designed …

Gene Set Enrichment And Projection: A Computational Tool For Knowledge Discovery In Transcriptomes, Karl Douglas Stamm

Dissertations (1934 -)

Explaining the mechanism behind a genetic disease involves two phases, collecting and analyzing data associated to the disease, then interpreting those data in the context of biological systems. The objective of this dissertation was to develop a method of integrating complementary datasets surrounding any single biological process, with the goal of presenting the response to a signal in terms of a set of downstream biological effects. This dissertation specifically tests the hypothesis that computational projection methods overlaid with domain expertise can direct research towards relevant systems-level signals underlying complex genetic disease. To this end, I developed a software algorithm named …

Investigation Into The Function Of Endothelial Cells And Their Signaling In Early Salivary Gland Development, Hae Ryong Kwon

Legacy Theses & Dissertations (2009 - 2024)

Functional vasculature regulates organ formation and regeneration. Perfusion-independent and nutrition-independent endothelial regulation of epithelial patterning is of considerable interest for application in restoring parenchymal function. During murine submandibular salivary gland development, the vasculature co-develops with the epithelium; however, it is still unknown if the vasculature has instructive effects on the epithelium. A systems biological study revealed that endothelial genes are enriched in epithelial clefts, suggesting a potential involvement of endothelial cells in early morphogenesis. Using immunodepletion of the endothelial cells from the mesenchyme of reconstituted glands, a requirement for endothelial cells in epithelial patterning was demonstrated. Specifically, lobule formation was …

Characterization Of Hemerythrin-Like Protein Rv2633c, Michelle D. Cherne

Honors Undergraduate Theses

Hemerythrin-like protein Rv2633c is a small 18 kDa protein that is expressed in Mycobacterium tuberculosis (Mtb). Sequence analysis of Rv2633c predicts the presence of a hemerythrin-like domain, which binds dioxygen using a µ-oxo-bridge (Fe-O-Fe), rather than a heme group. Though it is noticeably upregulated during macrophage infection and during in vitro acidification, the role of Rv2633c in Mtb survival has yet to be elucidated. This project aims to characterize the function of Rv2633c by studying the in vitro response of the recombinant protein to conditions present in the macrophage lysosome, such as reduced oxygen levels or the …

Interactomics-Based Functional Analysis: Using Interaction Conservation To Probe Bacterial Protein Functions, J. Harry Caufield

Theses and Dissertations

The emergence of genomics as a discrete field of biology has changed humanity’s understanding of our relationship with bacteria. Sequencing the genome of each newly-discovered bacterial species can reveal novel gene sequences, though the genome may contain genes coding for hundreds or thousands of proteins of unknown function (PUFs). In some cases, these coding sequences appear to be conserved across nearly all bacteria. Exploring the functional roles of these cases ideally requires an integrative, cross-species approach involving not only gene sequences but knowledge of interactions among their products. Protein interactions, studied at genome scale, extend genomics into the field of …

Evolution Of New Duplicate Genes In Arabidopsis Thaliana, Nicholas Curtis Marowsky

Wayne State University Theses

Abstract

Gene duplication is one of the major mechanisms by which organisms expand their genomes. The material added to the genome can then be acted upon by mutation and natural selection to increase the fitness of the species. By studying these duplicate sequences we can understand the process by which species evolve new functional genes. In a previous paper we identified 100 new duplicate genes through a genome wide comparison between A. thaliana and related species. We selected three of these new duplicate genes and investigated more closely their sequence and expression divergence from their parental gene. The three new …

Modeling Stem Cell Population Dynamics, Samiur Arif

Computer Science Theses & Dissertations

Because of the stochastic nature of biological systems, mathematical and computational modeling approaches have become more acceptable to experimentalists and clinicians in recent years as contributing to new understandings of complicated cell mechanisms and tissue physiology. Indeed, even single cell or small tissue samples are complex dynamic systems that adapt to environmental challenges in space and time which is poorly understood. Mathematical models and computer simulations can explain and uncover unknown aspects of cell behavior and tissue functions. Models based on key biological mechanisms can give interesting insights and formulate predictions that cannot be derived from physical experiments or statistical …

Isolation And Characterization Of Multipotent Lung Stem Cells From P53 Mutant Mice Models, Venkat Sundar Gadepalli

Theses and Dissertations

Recent advances in understanding lung biology have shown evidence for the existence of resident lung stem cells. Independent studies in identifying and characterizing these somatic lung stem cells have shown the potential role of these cells in lung repair and regeneration. Understanding the functional characteristics of these tissue resident stem/progenitor cells has gained much importance with increasing evidence of cancer stem cells, cells in a tumor tissue with stem cell characteristics. Lung cancer is most commonly characterized by loss of p53 function which results in uncontrolled cell divisions. Incidence of p53 point mutations is highest in lung cancer, with a …

An Investigation Of Alternative Oxidase Presence, Expression, And Regulation In The Moss Physcomitrella Patens, Karina I. Neimanis

Theses and Dissertations (Comprehensive)

Alternative oxidase (AOX) is an inner mitochondrial membrane protein that introduces a branch point at ubiquinone within the respiratory electron transport system (ETS). The AOX protein bypasses two sites of proton translocation within the ETS and as a result the yield of ATP per oxygen consumed is significantly reduced. Although AOX appears to be energetically wasteful, recent studies have revealed that AOX has a wide taxonomic distribution. AOX multigene families, transcripts, protein levels, and enzymatic activity have been most thoroughly characterized in many angiosperm (flowering) plants. Given the data available for angiosperm AOXs, evidence of non-angiosperm AOXs in the primary …

Gene Ontology Analysis Of Pairwise Genetic Associations In Two Genome-Wide Studies Of Sporadic Als, Nora Chung Kim, Peter C. Andrews, Folkert W. Asselbergs, H Robert Frost, Scott M. Williams, Brent T. Harris, Cynthia Read, Kathleen D. Askland, Jason H. Moore

Dartmouth Scholarship

It is increasingly clear that common human diseases have a complex genetic architecture characterized by both additive and nonadditive genetic effects. The goal of the present study was to determine whether patterns of both additive and nonadditive genetic associations aggregate in specific functional groups as defined by the Gene Ontology (GO).

Network To Pology In Human Protein Interaction Data Predicts Functional Association, Hua Li

Dissertations and Theses (Open Access)

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the …

Automated Isolation Of Translational Efficiency Bias That Resists The Confounding Effect Of Gc(At)-Content, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer

Kno.e.sis Publications

Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons is preferred. Detection of this bias is an important tool …

Joint Multiple Testing Procedures For Graphical Model Selection With Applications To Biological Networks, Houston N. Gilbert, Mark J. Van Der Laan, Sandrine Dudoit

U.C. Berkeley Division of Biostatistics Working Paper Series

Gaussian graphical models have become popular tools for identifying relationships between genes when analyzing microarray expression data. In the classical undirected Gaussian graphical model setting, conditional independence relationships can be inferred from partial correlations obtained from the concentration matrix (= inverse covariance matrix) when the sample size n exceeds the number of parameters p which need to estimated. In situations where n < p, another approach to graphical model estimation may rely on calculating unconditional (zero-order) and first-order partial correlations. In these settings, the goal is to identify a lower-order conditional independence graph, sometimes referred to as a ‘0-1 graphs’. For either choice of graph, model selection may involve a multiple testing problem, in which edges in a graph are drawn only after rejecting hypotheses involving (saturated or lower-order) partial correlation parameters. Most multiple testing procedures applied in previously proposed graphical model selection algorithms rely on standard, marginal testing methods which do not take into account the joint distribution of the test statistics derived from (partial) correlations. We propose and implement a multiple testing framework useful when testing for edge inclusion during graphical model selection. Two features of our methodology include (i) a computationally efficient and asymptotically valid test statistics joint null distribution derived from influence curves for correlation-based parameters, and (ii) the application of empirical Bayes joint multiple testing procedures which can effectively control a variety of popular Type I error rates by incorpo- rating joint null distributions such as those described here (Dudoit and van der Laan, 2008). Using a dataset from Arabidopsis thaliana, we observe that the use of more sophisticated, modular approaches to multiple testing allows one to identify greater numbers of edges when approximating an undirected graphical model using a 0-1 graph. Our framework may also be extended to edge testing algorithms for other types of graphical models (e.g., for classical undirected, bidirected, and directed acyclic graphs).

A Locus-Based Paradigm For Generating Systems Biological Inferences From Large Scale Functional Genomics Datasets, Ajish Dominic George

Legacy Theses & Dissertations (2009 - 2024)

Genomics data is growing at a exponential rate. The ability to integrate new results with existing knowledge about genomic biology is rapidly becoming the limiting factor as there no universal language with which to describe genomic functional elements. To integrate and compare new and existing genomic data, we define our basic functional unit of a genome to be a locus -- a set of positional coordinates along any genome with an arbitrary amount of functional annotations attached. The locus concept enables addressing genomic elements and annotations at any level of granularity from entire swaths of chromosomes to single base-positions. We …